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How to price a productized AI offer

Cost-plus, value-based, or outcome-based — and when to use each.

gulanonline@gmail.com 24 May 2026 1 min read

The most common pricing mistake in productized AI is anchoring to delivery cost instead of customer value.

Three pricing models

Cost-plus: calculate your delivery cost, add a margin. Safe. Boring. Leaves money on the table.
Value-based: price as a percentage of the value the customer captures. Higher ceiling, harder to justify upfront.
Outcome-based: price contingent on the outcome being achieved. Aligns incentives but introduces collection risk.

When each works

Cost-plus works for entry-level offers where the buyer is price-sensitive and the value is uncertain pre-purchase.

Value-based works for mid-market offers where the value is large and roughly knowable upfront.

Outcome-based works for enterprise offers where the value is huge, measurable, and you can afford the collection risk.

Our default

We default to value-based pricing. Our retainers, audits, and agent builds are all priced as a function of the revenue, cost-saving, or strategic value the client captures — not the hours we spend.

Anchoring

Always present three options. Buyers don’t know what a “good price” is in a new category — they triangulate from the prices you show them. Three options also defuses negotiation.

Stop watching demos. Start shipping leverage.

A 30-minute fit call is exactly that — a fit call. No deck. No sales theatre.